Screening and receiving information for intimate partner violence in healthcare settings: a cross-sectional study of Arab and Jewish women of childbearing age in Israel
Bibliographic record
Abstract
OBJECTIVES: We studied the proportion of women who have ever been screened (ES) for intimate partner violence (IPV) in a healthcare setting, received information (RI) about relevant services, or both, and explored disparities in screening and information provision by ethnicity and other characteristics. DESIGN: In 2014-2015, we undertook a cross-sectional study, conducting interviews using a structured questionnaire among a stratified sample of 1401 Arab and Jewish women in Israel. SETTING: A sample of 63 maternal and child health clinics (MCH) clinics in four geographical districts. PARTICIPANTS: Women aged 16-48 years, pregnant or up to 6 months after childbirth. PRIMARY AND SECONDARY OUTCOME MEASURES: We used multivariable generalised estimating equation analysis to determine characteristics of women who were ES (Has anyone at the healthcare services (HCS) ever asked you whether you have experienced IPV?); RI (Have you ever received information about what to do if you experience IPV?); and both (ES&RI). RESULTS: Less than half of participants (48.8%) reported ES; 50.5% RI; and 30% were both ES&RI. Having experienced any IPV was not associated with ES or ES&RI, but was associated with RI in an unexpected direction. Women at higher risk for IPV (Arab minority women, lower education, unmarried) were less likely to report being ES, RI or both. The OR and 95% CI for not ER&RI were: 1.58 (1.00 to 2.49) among Arab compared with Jewish women; 1.95 (1.42 to 2.66) among low education versus academic education women; 1.34 (1.03 to 1.73) among not working versus working. ES, RI and both differ across districts. CONCLUSIONS: While Israel mandates screening and providing information regarding IPV for women visiting the HCS, we found inequalities, suggesting inconsistencies in policy implementation and missed opportunities to detect IPV. To increase IPV screening and information provision, the ministry of health should circulate clarification and provide support to healthcare providers to conduct these activities.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".